Robot Impedance Control and Passivity Analysis with Inner Torque and Velocity Feedback Loops

Impedance control is a well-established technique to control interaction forces in robotics. However, real implementations of impedance control with an inner loop may suffer from several limitations. Although common practice in designing nested control systems is to maximize the bandwidth of the inner loop to improve tracking performance, it may not be the most suitable approach when a certain range of impedance parameters has to be rendered. In particular, it turns out that the viable range of stable stiffness and damping values can be strongly affected by the bandwidth of the inner control loops (e.g. a torque loop) as well as by the filtering and sampling frequency. This paper provides an extensive analysis on how these aspects influence the stability region of impedance parameters as well as the passivity of the system. This will be supported by both simulations and experimental data. Moreover, a methodology for designing joint impedance controllers based on an inner torque loop and a positive velocity feedback loop will be presented. The goal of the velocity feedback is to increase (given the constraints to preserve stability) the bandwidth of the torque loop without the need of a complex controller.Comment: 14 pages in Control Theory and Technology (2016

Human Like Adaptation of Force and Impedance in Stable and Unstable Tasks

Abstract—This paper presents a novel human-like learning con-troller to interact with unknown environments. Strictly derived from the minimization of instability, motion error, and effort, the controller compensates for the disturbance in the environment in interaction tasks by adapting feedforward force and impedance. In contrast with conventional learning controllers, the new controller can deal with unstable situations that are typical of tool use and gradually acquire a desired stability margin. Simulations show that this controller is a good model of human motor adaptation. Robotic implementations further demonstrate its capabilities to optimally adapt interaction with dynamic environments and humans in joint torque controlled robots and variable impedance actuators, with-out requiring interaction force sensing. Index Terms—Feedforward force, human motor control, impedance, robotic control. I

Robust Whole-Body Motion Control of Legged Robots

We introduce a robust control architecture for the whole-body motion control of torque controlled robots with arms and legs. The method is based on the robust control of contact forces in order to track a planned Center of Mass trajectory. Its appeal lies in the ability to guarantee robust stability and performance despite rigid body model mismatch, actuator dynamics, delays, contact surface stiffness, and unobserved ground profiles. Furthermore, we introduce a task space decomposition approach which removes the coupling effects between contact force controller and the other non-contact controllers. Finally, we verify our control performance on a quadruped robot and compare its performance to a standard inverse dynamics approach on hardware.Comment: 8 Page

Planning and Real Time Control of a Minimally Invasive Robotic Surgery System

This paper introduces the planning and control software of a teleoperating robotic system for minimally invasive surgery. It addresses the problem of how to organize a complex system with 41 degrees of freedom including robot setup planning, force feedback control and nullspace handling with three robotic arms. The planning software is separated into sequentially executed planning and registration procedures. An optimal setup is first planned in virtual reality and then adapted to variations in the operating room. The real time control system is composed of hierarchical layers. The design is flexible and expandable without losing performance. Structure, functionality and implementation of planning and control are described. The robotic system provides the surgeon with an intuitive hand-eye-coordination and force feedback in teleoperation for both hands

Force Control of a Unilateral Master-Slave System Using a SCARA Robot Arm

Industrial manipulators have several applications in a multitude of disciplines. The use of industrial manipulators has increased rapidly, and they are more refined in many applications due to advances such as fast response time, high precision, quick speed and a high level of performance. Most industrial manipulators are position-controlled; usually vision and force sensors are not integrated in most commercial industrial robots. Therefore, the addition of force and vision sensing mechanisms is required to successfully automate advanced tasks, and to enable robots to avoid high contact forces while working in applications that require contact with environments. The objective of this thesis is to implement a unilateral master-slave system for medical applications. In this thesis, a Polaris Vicra® optical tracking device is used to represent the master system, while a four degree of freedom (DOF) position-controlled SCARA manipulator from Epson is used to represent the slave system. The manipulator is equipped with a force-torque sensor to facilitate operation in unknown environments. In addition, MapleSim is used to find the dynamic model for the SCARA manipulator. Furthermore, MapleSim is also used to validate the control algorithm prior to implementation on the hardware. Three force control techniques are used in this research and the robot's performance are evaluated. The control techniques are impedance control, admittance control and fuzzy logic control. The admittance and fuzzy logic controllers are applied to the proposed master-slave system while the impedance control is applied to the manipulator model, which was obtained from MapleSim. In order to validate the presented control algorithms, several experiments and simulations were carried out. The experimental results show the ability of the presented controllers (admittance and fuzzy logic) to track the operator signal while keeping the force within the desired range. The simulation and animation of the impedance controller on the other hand, shows that the robot's performance can be evaluated through software

Effects of Impedance Reduction of a Robot for Wrist Rehabilitation on Human Motor Strategies in Healthy Subjects during Pointing Tasks

Studies on human motor control demonstrated the existence of simplifying strategies (namely `Donders' law') adopted to deal with kinematically redundant motor tasks. In recent research we showed that Donders' law also holds for human wrist during pointing tasks, and that it is heavily perturbed when interacting with a highly back-drivable state-of-the-art rehabilitation robot. We hypothesized that this depends on the excessive mechanical impedance of the Pronation/Supination (PS) joint of the robot and in this work we analyzed the effects of its reduction. To this end we deployed a basic force control scheme, which minimizes human-robot interaction force. This resulted in a 70% reduction of the inertia in PS joint and in decrease of 81% and 78% of the interaction torques during 1-DOF and 3-DOFs tasks. To assess the effects on human motor strategies, pointing tasks were performed by three subjects with a lightweight handheld device, interacting with the robot using its standard PD control (setting impedance to zero) and with the force-controlled robot. We quantified Donders' law as 2-dimensional surfaces in the 3-dimensional configuration space of rotations. Results revealed that the subject-specific features of Donders' surfaces reappeared after the reduction of robot impedance obtained via the force control